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Remove rows with all or some NAs (missing values) in data.frame
...ul mmus rnor cfam
2 ENSG00000199674 0 2 2 2 2
6 ENSG00000221312 0 1 2 3 2
na.omit is nicer for just removing all NA's. complete.cases allows partial selection by including only certain columns of the dataframe:
> final[complete.cases(final[ , 5:6]),]
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What Process is using all of my disk IO
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edited Dec 7 '14 at 14:13
Aaron Digulla
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a...
Pandas percentage of total with groupby
...d
np.random.seed(0)
df = pd.DataFrame({'state': ['CA', 'WA', 'CO', 'AZ'] * 3,
'office_id': list(range(1, 7)) * 2,
'sales': [np.random.randint(100000, 999999)
for _ in range(12)]})
state_office = df.groupby(['state', 'office_id']).agg...
Numpy: Get random set of rows from 2D array
...
>>> A = np.random.randint(5, size=(10,3))
>>> A
array([[1, 3, 0],
[3, 2, 0],
[0, 2, 1],
[1, 1, 4],
[3, 2, 2],
[0, 1, 0],
[1, 3, 1],
[0, 4, 1],
[2, 4, 2],
[3, 3, 1]])
>>> idx = np.ran...
RegEx to parse or validate Base64 data
... the following:
^(?:[A-Za-z0-9+/]{4})*(?:[A-Za-z0-9+/]{2}==|[A-Za-z0-9+/]{3}=)?$
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This is the effect I'm trying to achieve with Bootstrap 3 carousel
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How assignment works with Python list slice?
...ete, or replace contents from a list:
Insertion:
>>> a = [1, 2, 3]
>>> a[0:0] = [-3, -2, -1, 0]
>>> a
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Deletion:
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>>> a
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A pattern that often came up in Python was
bar = []
for item in some_iterable:
bar.append...